Data capture instructions for asset tracking

ABSTRACT

Methods, systems, and devices for data capture instructions for asset tracking are provided. An example method for capturing data involves obtaining raw data from a data source onboard an asset and monitoring the raw data for satisfaction of a simplified data capture trigger. When the simplified data capture trigger is satisfied, a dataset simplification algorithm is performed on the raw data to generate a simplified set of raw data, and the simplified set of raw data is logged. The method further involves monitoring the raw data for satisfaction of a rich data capture trigger. When the rich data capture trigger is satisfied, an unsimplified block of raw data is identified and logged for rich data analysis. The data is transmitted to a server. The unsimplified block of raw data contains raw data that is additional to the raw data contained in the simplified set of raw data.

RELATED APPLICATIONS

This application claims the benefit under 35 U.S.C. § 119(e) to U.S.Provisional Application Ser. No. 63/039,659, titled “Data CaptureInstructions And Trigger Configuration For Asset Tracking Devices”,filed on Jun. 16, 2020, which is herein incorporated by reference in itsentirety.

FIELD

The present disclosure relates to telematics, and in particular to assettracking for telematics systems and the processing of data collectedtherefor.

BACKGROUND

A telematics system may track the location of an asset, such as avehicle, and other data related to the asset, directly through the assetor through an asset tracking device located onboard the asset. Theasset, or its asset tracking device, may communicate with a satellitenavigation system, such as a Global Positioning System (GPS), GlobalNavigation Satellite System (GNSS), cellular tower network, Wi-Finetwork, or other system to track the location of the asset. An assettracking device may collect additional information via sensors on theasset tracking device, such as accelerometer data or other data. Anasset tracking device may also collect information through a dataconnection with the asset itself, such as, in the case of a vehicularasset, through an onboard diagnostic port from which engine speed,battery temperature, fuel level, tire pressure, outside temperature, orother asset data may be obtained. Such data may be received and recordedby technical infrastructure of the telematics system and used in theprovision of fleet management tools, other telematics services, or forfurther data analysis.

SUMMARY

According to an aspect of the disclosure, a method for capturing datafrom an asset or asset tracking device is provided. The method involvesobtaining raw data from a data source onboard an asset and monitoringthe raw data for satisfaction of a simplified data capture trigger. Themethod further involves, when the simplified data capture trigger issatisfied, performing a dataset simplification algorithm on the raw datato generate a simplified set of raw data, and logging the simplified setof raw data, and monitoring the raw data for satisfaction of a rich datacapture trigger. The method further involves, when the rich data capturetrigger is satisfied, identifying and logging an unsimplified block ofraw data for rich data analysis. The unsimplified block of raw dataspans a data window that covers a time at which the rich data capturetrigger was satisfied. The unsimplified block of raw data contains rawdata that is additional to the raw data contained in the simplified setof raw data. The method further involves transmitting the simplified setof raw data and the unsimplified block of raw data to a server.

Monitoring the raw data for satisfaction of the rich data capturetrigger may involve evaluating the rich data capture trigger for a firstdata type, and the unsimplified block of raw data may include raw dataof the first data type. Evaluation of the rich data capture trigger mayinclude one or more of determining whether a value of a data point inthe raw data of the first data type surpasses a first threshold value,and determining whether a composite value of a group of data points inthe raw data of the first data type that spans an evaluation windowsurpasses a second threshold value. The unsimplified block of raw datafurther may include raw data of a second data type different from thefirst data type. The raw data of the second data type may span asupplementary data window that is greater in duration than the datawindow that is spanned by the raw data of the first data type. The assetmay include a vehicle, the first data type may include a vehicleaccelerometer data, and the second data type may include vehicle speeddata or vehicle location data. The simplified set of raw data is to beprocessed for telematics services, and wherein the method furthercomprises flagging the unsimplified block of raw data for rich dataanalysis separate from processing of the simplified set of raw data forthe telematics services. The rich data analysis may include machinelearning analysis. The data source may include one or more of: anonboard diagnostic port of the asset, a locating device of the asset, alocating device of an asset tracking device onboard the asset, a sensorof the asset, and a sensor of an asset tracking device onboard theasset. The method may further involve buffering the raw data in a rawdata buffer where the raw data is monitored for satisfaction of thesimplified data capture trigger and the rich data capture trigger. Thedataset simplification algorithm may include a line simplificationalgorithm that reduces a curve of raw data composed of line segmentsinto a similar curve with fewer points.

According to another aspect of the disclosure, an asset tracking deviceis provided. The asset tracking device includes an interface layer toobtain raw data from a data source onboard an asset, a memory to storethe raw data, and a controller to execute simplified data captureinstructions. The controller executes the simplified data captureinstructions to monitor the raw data for satisfaction of a simplifieddata capture trigger, and when the simplified data capture trigger issatisfied, perform a dataset simplification algorithm on the raw data togenerate a simplified set of raw data and log the simplified set of rawdata. The controller also executes rich data capture instructions tomonitor the raw data for satisfaction of a rich data capture trigger,when the rich data capture trigger is satisfied, identify and log anunsimplified block of raw data for rich data analysis. The unsimplifiedblock of raw data spans a data window that covers a time at which therich data capture trigger was satisfied. The unsimplified block of rawdata contains raw data that is additional to the raw data contained inthe simplified set of raw data. The asset tracking device furtherincludes a communication interface to transmit the simplified set of rawdata and the unsimplified block of raw data to a server.

The asset tracking device may include a raw data buffer to store the rawdata to be monitored for satisfaction of the simplified data capturetrigger and the rich data capture trigger. The asset tracking device mayinclude logging memory to store the logged simplified set of raw dataand the logged unsimplified block of raw data prior to transmission bythe communication interface to the server. The asset tracking device mayfurther include a sensor to gather sensor data at the asset trackingdevice, and a locating device to obtain location data of the assettracking device, wherein the data source comprises the sensor, thelocating device, or an onboard diagnostic port of the asset, and whereinthe interface layer comprises a first interface to obtain the sensordata from the sensor, a second interface to obtain the location datafrom the locating device, and a third interface to obtain asset datafrom the onboard diagnostic port.

According to yet another aspect of the disclosure, a non-transitorymachine-readable storage medium is provided. The non-transitorymachine-readable storage medium stores instructions that when executedcause a controller of an asset or asset tracking device to obtain rawdata from a data source onboard the asset and monitor the raw data forsatisfaction of a simplified data capture trigger. The instructionsfurther cause the controller to, when the simplified data capturetrigger is satisfied, perform a dataset simplification algorithm on theraw data to generate a simplified set of raw data, and log thesimplified set of raw data. The instructions further cause thecontroller to monitor the raw data for satisfaction of a rich datacapture trigger, and when the rich data capture trigger is satisfied,identify and log an unsimplified block of raw data for rich dataanalysis. The unsimplified block of raw data spans a data window thatcovers a time at which the rich data capture trigger was satisfied. Theunsimplified block of raw data contains raw data that is additional tothe raw data contained in the simplified set of raw data. Theinstructions further cause the controller to transmit the simplified setof raw data and the unsimplified block of raw data to a server.

The instructions may further cause the controller to monitor the rawdata for satisfaction of the rich data capture trigger by evaluating therich data capture trigger for a first data type, wherein theunsimplified block of raw data comprises raw data of the first datatype. Evaluation of the rich data capture trigger may include one ormore of: determining whether a value of a data point in the raw data ofthe first data type surpasses a first threshold value, and determiningwhether a composite value of a group of data points in the raw data ofthe first data type that spans an evaluation window surpasses a secondthreshold value. The unsimplified block of raw data may further includeraw data of a second data type different from the first data type. Thesimplified set of raw data may be processed for telematics services, andw the instructions may further cause the controller to flag theunsimplified block of raw data for rich data analysis separate fromprocessing of the simplified set of raw data for the telematicsservices.

According to yet another aspect of the disclosure, another method forcapturing data from an asset or asset tracking device is provided. Themethod involves obtaining a rich data capture trigger that defines whena controller of an asset or an asset tracking device onboard the assetis to identify and log an unsimplified block of raw data in raw data onthe asset tracking device for rich data analysis. The raw data isobtained by the asset tracking device from a data source onboard theasset. The method further involves transmitting data captureinstructions to the asset tracking device. The data capture instructionscontain the rich data capture trigger. The data capture instructionscause a controller of the asset tracking device to monitor the raw datafor satisfaction of a simplified data capture trigger, and, when thesimplified data capture trigger is satisfied, perform a datasetsimplification algorithm on the raw data to generate a simplified set ofraw data, and log the simplified set of raw data. The data captureinstructions further cause the controller to monitor the raw data forsatisfaction of a rich data capture trigger, and, when the rich datacapture trigger is satisfied, identify and log an unsimplified block ofraw data for rich data analysis. The unsimplified block of raw dataspans a data window that covers a time at which the rich data capturetrigger was satisfied. The unsimplified block of raw data contains rawdata that is additional to the raw data contained in the simplified setof raw data. The method further involves receiving the simplified set ofraw data and the unsimplified block of raw data from the asset trackingdevice.

The method may further involve providing a user interface to configurethe rich data capture trigger, wherein the rich data capture trigger isobtained by configuration through the user interface. The user interfacemay further be to configure the data window. The data captureinstructions may cause the controller to monitor the raw data forsatisfaction of the rich data capture trigger by evaluating the richdata capture trigger for a first data type, the unsimplified block ofraw data may include raw data of the first data type, and the userinterface may further be to configure selection of the first data type.Evaluation of the rich data capture trigger may include one or more of:determining whether a value of a data point in the raw data of the firstdata type surpasses a first threshold value, wherein the user interfaceis further to configure the first threshold value, and determiningwhether a composite value of a group of data points in the raw data ofthe first data type that spans an evaluation window surpasses a secondthreshold value, wherein the user interface is further to configure thesecond threshold value. The unsimplified block of raw data may furtherinclude raw data of a second data type different from the first datatype, and the user interface may further be to configure selection ofthe second data type. The raw data of the second data type may span asupplementary data window that is greater in duration than the datawindow that is spanned by the raw data of the first data type, and theuser interface may further be to configure the supplementary datawindow. The unsimplified block of raw data may be flagged by the assettracking device for separate treatment from the simplified set of rawdata, and the method may further involve processing the simplified setof raw data for telematics services and performing rich data analysis onthe unsimplified block of raw data.

According to yet another aspect of the disclosure, a system forcapturing data from assets or asset tracking devices is provided. Thesystem includes an asset tracking device onboard an asset. The assettracking device is configured to obtain raw data from a data sourceonboard the asset, monitor the raw data for satisfaction of a simplifieddata capture trigger, and, when the simplified data capture trigger issatisfied, perform a dataset simplification algorithm on the raw data togenerate a simplified set of raw data and log the simplified set of rawdata. The asset tracking device is further configured to monitor the rawdata for satisfaction of a rich data capture trigger, and, when the richdata capture trigger is satisfied, identify and log an unsimplifiedblock of raw data for rich data analysis. The unsimplified block of rawdata spans a data window that covers a time at which the rich datacapture trigger was satisfied. The unsimplified block of raw datacontains raw data that is additional to the raw data contained in thesimplified set of raw data. The asset tracking device is furtherconfigured to transmit the simplified set of raw data and theunsimplified block of raw data. The system further includes one or moreservers to obtain the rich data capture trigger, transmit data captureinstructions to the asset tracking device, the data capture instructionscontaining the rich data capture trigger, receive the simplified set ofraw data and the unsimplified block of raw data from the asset trackingdevice.

The one or more servers may further be to provide a user interface toconfigure the rich data capture trigger, wherein the rich data capturetrigger is obtained by configuration through the user interface. Theuser interface may further be to configure the data window. The datacapture instructions may cause the asset tracking device to monitor theraw data for satisfaction of the rich data capture trigger by evaluatingthe rich data capture trigger for a first data type, the unsimplifiedblock of raw data may include raw data of the first data type, and theuser interface may further be to configure selection of the first datatype. Evaluation of the rich data capture trigger may include one ormore of: determining whether a value of a data point in the raw data ofthe first data type surpasses a first threshold value, wherein the userinterface is further to configure the first threshold value, anddetermining whether a composite value of a group of data points in theraw data of the first data type that spans an evaluation windowsurpasses a second threshold value, wherein the user interface isfurther to configure the second threshold value. The unsimplified blockof raw data may further include raw data of a second data type differentfrom the first data type, and the user interface may further ne toconfigure selection of the second data type. The raw data of the seconddata type may span a supplementary data window that is greater induration than the data window that is spanned by the raw data of thefirst data type, wherein the user interface is further to configure thesupplementary data window. The unsimplified block of raw data may beflagged by the asset tracking device for separate treatment from thesimplified set of raw data, and the one or more servers may include atelematics services module to process the simplified set of raw data,and a rich data analysis module to perform rich data analysis on theunsimplified block of raw data.

According to another aspect of a disclosure, another non-transitorymachine-readable storage medium is provided. The non-transitorymachine-readable storage medium includes data capture controlinstructions that when executed cause a processor of a computing deviceto obtain a rich data capture trigger that defines when a controller ofan asset tracking device onboard an asset is to identify and log anunsimplified block of raw data in raw data on the asset tracking devicefor rich data analysis, the raw data obtained by the asset trackingdevice from a data source onboard the asset, and transmit data captureinstructions to the asset tracking device, the data capture instructionscontaining the rich data capture trigger. The data capture instructionscause a controller of the asset tracking device to monitor the raw datafor satisfaction of a simplified data capture trigger, and, when thesimplified data capture trigger is satisfied, perform a datasetsimplification algorithm on the raw data to generate a simplified set ofraw data, and log the simplified set of raw data. The data captureinstructions further cause the controller to monitor the raw data forsatisfaction of a rich data capture trigger, and when the rich datacapture trigger is satisfied, identify and log an unsimplified block ofraw data for rich data analysis and log the unsimplified block of rawdata. The unsimplified block of raw data spans a data window that coversa time at which the rich data capture trigger was satisfied. Theunsimplified block of raw data contains raw data that is additional tothe raw data contained in the simplified set of raw data. The datacapture control instructions further cause the processor of thecomputing device to receive the simplified set of raw data and theunsimplified block of raw data from the asset tracking device.

The data capture instructions may cause the controller to monitor theraw data for satisfaction of the rich data capture trigger by evaluatingthe rich data capture trigger for a first data type, the unsimplifiedblock of raw data may include raw data of the first data type, and thedata capture control instructions may further cause the processor toprovide a user interface to configure the rich data capture trigger, thedata window, and selection of the first data type, wherein the rich datacapture trigger is obtained by configuration through the user interface.Evaluation of the rich data capture trigger may include one or more of:determining whether a value of a data point in the raw data of the firstdata type surpasses a first threshold value, wherein the user interfaceis further to configure the first threshold value, and determiningwhether a composite value of a group of data points in the raw data ofthe first data type that spans an evaluation window surpasses a secondthreshold value, wherein the user interface is further to configure thesecond threshold value. The unsimplified block of raw data further mayinclude raw data of a second data type different from the first datatype, the raw data of the second data type may span a supplementary datawindow that is greater in duration than the data window that is spannedby the raw data of the first data type, and the user interface mayfurther be to configure selection of the second data type and thesupplementary data window.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram of an example system for capturing datafrom an asset or asset tracking device.

FIG. 2 is a block diagram of an example asset tracking device thatcaptures simplified data for a telematics service and rich data for richdata analysis.

FIG. 3 is a flowchart of an example method for capturing data from anasset or asset tracking device.

FIG. 4A is a data plot displaying example raw data collected at an assetor asset tracking device.

FIG. 4B is a data plot displaying an example simplified set of raw dataderived from the application of a dataset simplification algorithm tothe raw data of FIG. 4A.

FIG. 4C is a data plot displaying example unsimplified blocks of rawdata derived from the application of a raw data capture algorithm to theraw data of FIG. 4A.

FIG. 5 is a data plot displaying an example hybridized set of raw datathat combines the simplified set of raw data of FIG. 4B and theunsimplified blocks of raw data of FIG. 4C.

FIG. 6 is a block diagram of another example asset tracking device thatcaptures simplified data and rich data, the asset tracking deviceincluding a raw data buffer that receives raw data through a sensoronboard the asset tracking device, a locating device onboard the assettracking device, and an on-board diagnostic port of the asset.

FIG. 7 is a block diagram of example non-transitory machine-readablestorage medium that contains simplified data capture instructions andrich data capture instructions.

FIG. 8 is another data plot displaying another example hybridized set ofraw data, the data plot showing differently sized data windowscorresponding to different raw data types collected in unsimplifiedblocks of raw data.

FIG. 9 is a schematic diagram of another example system for capturingdata from assets or asset tracking devices, the system including a datacapture trigger configuration module to configure rich data capturetriggers.

FIG. 10 is a flowchart of an example method for capturing data from anasset or asset tracking device that involves transmission of a rich datacapture trigger to the asset tracking device.

FIG. 11 is a schematic diagram of an example user interface to configurea rich data capture trigger for execution at an asset or asset trackingdevice.

FIG. 12 is a block diagram of another example asset tracking device.

FIG. 13 is a flowchart of another example method for capturing data froman asset or asset tracking device.

DETAILED DESCRIPTION

A large telematics system may collect data from a very high number ofassets, either directly or through asset tracking devices. An assettracking device may refer to a self-contained device installed at anasset, or a tracking device that is integrated into the asset itself. Ineither case, it may be said that data is being captured by an assettracking device. These asset tracking devices may be capable ofcollecting such large amounts of raw data that the technicalinfrastructure of the telematics system could be overwhelmed if all ofthe data that is collected by the devices were to be transmitted to, andprocessed by, the telematics system. Therefore, asset tracking devicesin telematics systems generally transmit only a small proportion of thetotal number of data points collected for processing, and discard theremainder.

An asset tracking device may determine which points to transmit forprocessing and which data points to discard in a number of ways. Forexample, the asset tracking device may employ simple periodic sampling,whereby only the data that is collected at regularly spaced timeintervals is retained for transmission. Alternatively, the data that istransmitted may be selected algorithmically by a dataset simplificationalgorithm, whereby only the most significant data points aretransmitted. Thus, an asset tracking device may run a datasetsimplification algorithm prior to transmitting data to a telematicssystem to reduce the data collection and processing load on thetelematics system while ensuring that the transmitted data maintains asignificant degree of utility.

The level of detail in the dataset that results from a datasetsimplification algorithm may be tuned to be sufficient for fleetmanagement tools and other telematics services without being undulyburdensome to the technical infrastructure of the telematics system.However, this simplified data may lack rich detail the that may be ofinterest for more advanced analytical techniques. Thus, an assettracking device that only transmits data that has been passed through adataset simplification algorithm may be unable to provide the levels ofrich raw data to enable certain advanced analytics techniques, such asmachine learning analysis.

The present disclosure provides techniques for capturing data from anasset tracking device that is sufficiently detailed for a telematicsservice without overburdening the technical infrastructure of thetelematics system, while also capturing sufficiently rich raw data foranalytical purposes. These techniques involve an asset tracking deviceapplying a dataset simplification algorithm to the raw data it collectsin parallel with a rich data capture algorithm. The asset trackingdevice employs a dataset simplification algorithm to sparingly selectdata points suitable for a telematics service, while also monitoring theraw data for the satisfaction of rich data capture triggers in which theraw data exhibits particular signal features that warrant furtherin-depth analysis. When a rich data capture trigger is satisfied, theasset tracking device captures a block of raw data that has not beensimplified by the dataset simplification algorithm for further analysis,and forwards the rich block of raw data to the telematics system forfurther processing.

The application of a rich data capture algorithm in parallel with adataset simplification algorithm may enable the asset tracking device tocapture rich detail around select incidents that would have otherwisebeen missed by the dataset simplification algorithm. For example, in thecase of an asset tracking device tracking a vehicle travelling down abumpy road, a dataset simplification algorithm would typically avoidlogging small bumps and other perturbations in accelerometer data.However, a rich data capture algorithm may be configured to monitor thesame raw data that is being fed through the dataset simplificationalgorithm for particularly interesting features in the accelerometerdata—such as a signal feature that is indicative of the vehicletravelling over a pothole—and capture a rich block of raw accelerometerdata when the particular signal feature is detected that more thoroughlydescribes the event. The block of raw data may provide significantlygreater insight into the circumstances surrounding the pothole incidentthan would have been apparent in the data produced by the datasetsimplification algorithm. The rich data collected by the rich datacapture algorithm may be fed into machine learning models and otheranalyses for which there may otherwise be insufficient quantities ofdata to support.

Any adverse impacts to the technical infrastructure of the telematicssystem caused by the transmission of large blocks of raw data may becontrolled by configuring the rich data capture trigger to capture onlya narrow window of data surrounding the event. Thus, the technicalinfrastructure of the telematics system may collect small snippets ofrich raw data covering particularly interesting periods of time withoutundue burden. Further, these rich data capture triggers may beconfigured remotely and pushed to select groups of asset trackingdevices on-demand and on a device-by-device so the data collection ofthe telematics system as a whole is not largely affected by anyexperimental studies using rich data capture triggers. Thus, atelematics system may remain efficient in its collection of data tosupport its telematics services without missing opportunities for morerigorous data analysis.

FIG. 1 is a schematic diagram of an example system 100 for capturingdata from an asset or asset tracking device. The system 100 includes anasset tracking device 110 installed at an asset 102. The asset trackingdevice 110 collects data, such as the location of the asset trackingdevice 110 and sensor data from sensors onboard the asset trackingdevice 110. In some examples, such as in the case where the asset 102 isa vehicle, the asset tracking device 110 collects asset data directlyfrom the asset 102 through an onboard diagnostic port. This data isindicated generally as raw data 104.

For collecting location data, the system 100 may further include alocating system (not shown) for tracking the locations of one or moreasset tracking devices, including the asset tracking device 110, such asa Global Positioning System (GPS), a Global Navigation Satellite System(GNSS), a cellular tower network, Wi-Fi networks, or another systemwhich enables the monitoring of the location of asset tracking devices.

For exemplary purposes, the asset 102 is shown as a vehicular asset: atransport truck. However, the asset 102 may include any type ofvehicular asset, such as a passenger vehicle, construction vehicle,other utility vehicle, naval vessel, airplane, or any other vehicularasset that may be tracked by an asset tracking device. The asset 102 mayalso include any non-vehicular asset, such as a transport trailer,shipping container, pallet, shipped good, or any other asset which maybe tracked by an asset tracking device. Further, in other examples, theasset 102 may include a vehicle or other asset that includes anintegrated tracking device (the asset tracking device 110) to capturedata related to the asset 102.

The system 100 further includes technical infrastructure of a telematicssystem, indicated as the telematics system 120. The telematics system120 records location data, travel histories, and other data captured byasset tracking devices, including the asset tracking device 110. Thetelematics system 120 stores information collected from the assettracking devices, such as location data, accelerometer data, gyroscopedata, temperature sensor data, vehicle speed data, or any other datacollected by an asset tracking device. The telematics system 120 mayfurther store user accounts and other data associated with the assettracking devices for the provision of telematics services.

The technical infrastructure of the telematics system 120 includes oneor more computing devices, indicated, for example, as a server 122. Theserver 122 includes a communication interface to communicate with assettracking devices via one or more computing networks and/ortelecommunication networks, a memory to store data, and a controller toexecute the methods performed by the telematics system 120 as describedherein. For example, the server 122 is shown to provision a telematicsservices module 124 which provides telematics services to client devices(not shown) using data collected from asset tracking devices. The server122 is further shown to provision a rich data analysis module 126 whichmay be employed to analyze data collected from asset tracking devices,as will be discussed in greater detail below.

A portion of the raw data 104 collected by the asset tracking device 110is transmitted to the telematics system 120, indicated as transmitteddata 112. The transmitted data 112 includes a simplified set of raw data114 for the provision of telematics services, for example, at thetelematics services module 124. The transmitted data 112 furtherincludes an unsimplified block of raw data 116 for rich data analysis,for example, at the rich data analysis module 126. The simplified set ofraw data 114 is derived from the application of a dataset simplificationalgorithm on the raw data 104 collected by the asset tracking device110. By running a dataset simplification algorithm, only the significantpoints of data are transmitted to the telematics system 120 withoutoverburdening its technical infrastructure. However, rich raw data thatone may wish to obtain from the asset tracking device 110 may bedeliberately excluded by such dataset simplification algorithms. Thus,the asset tracking device 110 also runs a rich data capture algorithm toobtain the unsimplified block of raw data 116 from the raw data 104 forrich data analysis. This rich data capture algorithm may run in parallelwith the dataset simplification algorithm used to generate thesimplified set of raw data 114. Example methods by which the assettracking device 110 obtains and transmits such data are discussed ingreater detail below.

FIG. 2 is a block diagram of an example asset tracking device 200 thatcaptures simplified data and rich data. The asset tracking device 200may be understood to be one example of the asset tracking device 110 ofFIG. 1. The asset tracking device 200 is onboard an asset 202, which maybe similar to the asset 102 of FIG. 1.

The asset tracking device 200 includes an interface layer 210 to obtainraw data from a data source onboard the asset 202. The data source mayinclude a sensor of the asset tracking device 200, a sensor of the asset202, a locating device of the asset tracking device 200 (e.g., a GPSdevice located on the asset tracking device 200), a locating device ofthe asset 202 (e.g., a GPS device located on the asset), or, in examplesin which the asset 202 is a vehicle, an onboard diagnostic port of theasset 202. In any case, the interface layer 210 obtains raw data fromsuch a data source and includes one or more interfaces for receiving rawdata from the data source.

The asset tracking device 200 further includes a memory 220 that storesat least a portion of the raw data collected through the interface layer210, including a simplified set of raw data 222 and an unsimplifiedblock of raw data 224. As discussed herein, the simplified set of rawdata 222 is derived from a dataset simplification algorithm, and theunsimplified block of raw data 224 is derived from a rich data capturealgorithm. The memory 220 may include read-only memory (ROM),random-access memory (RAM), flash memory, magnetic storage, opticalstorage, and similar, or any combination thereof. Although only a singlesimplified set of raw data 222 and a single unsimplified block of rawdata 224 are shown, this is for illustrative purposes only, and it is tobe understood that the memory 220 may contain several simplified sets ofraw data 222 and several unsimplified blocks of raw data 224 at a time.The number of such data sets and data blocks stored on the memory 220 atany given time may depend on a number of factors, such as the memorysize of the memory 220, the frequency with which such data are logged,and the frequency with which such data are transmitted to a telematicssystem.

The asset tracking device 200 further includes a controller 230 toexecute simplified data capture instructions 232 and rich data captureinstructions 234. The controller includes one or more of a processor,microprocessor, microcontroller (MCU), central processing unit (CPU),processing core, state machine, logic gate array, application-specificintegrated circuit (ASIC), field-programmable gate array (FPGA), orsimilar, capable of executing, whether by software, hardware, firmware,or a combination of such, the actions performed by the controller 230 asdescribed herein. The controller 230 includes a memory, which mayinclude ROM, RAM, flash memory, magnetic storage, optical storage, andsimilar, or any combination thereof, for storing instructions and dataas discussed herein, including the simplified data capture instructions232 and rich data capture instructions 234.

The simplified data capture instructions 232 cause the controller 230 tomonitor the raw data collected by the asset tracking device 200 forsatisfaction of a simplified data capture trigger, and, when thesimplified data capture trigger is satisfied, perform a datasetsimplification algorithm on the raw data to generate the simplified setof raw data 222, and, log the simplified set of raw data 222.

The simplified data capture trigger may be triggered based on hardwarelimitations of the asset tracking device 200, such as, for example, whena raw data buffer reaches a limit to the amount of raw data it canstore, or based on telematics service standards, such as, for example, afrequency with which the data at the telematics system is to be updated.Example simplified data capture triggers are described with reference toFIG. 7, below.

The dataset simplification algorithm determines which data points shouldbe recorded for transmission to the telematics system (i.e., the datapoints that are most useful to providing a telematics service), andwhich data points should be discarded (i.e., the data points whichprovide little useful information to a telematics service). The datasetsimplification algorithm may include a line simplification algorithmthat reduces a curve of raw data composed of line segments into asimilar curve with fewer points. An example of such a linesimplification algorithm is the Ramer-Douglas-Peucker algorithm.

The rich data capture instructions 234 cause the controller 230 tomonitor the raw data for satisfaction of a rich data capture trigger,and when the rich data capture trigger is satisfied, identify and logthe unsimplified block of raw data 224 for rich data analysis.

The rich data capture trigger is a trigger that detects a feature of theraw data that warrants further analysis (e.g., a significant disturbancein kinematic sensor data), and causes a block of raw data that capturesthe event to be stored and transmitted to the telematics system.Evaluation of the raw data capture trigger may involve determiningwhether a value of a data point in the raw data of the first data typesurpasses a threshold value (e.g., when accelerometer data in the Z axisexceeds 2.5 g), determining whether a composite value of a group of datapoints in the raw data of the first data type that spans an evaluationwindow surpasses a threshold value (e.g., when a change in enginevoltage of greater than 0.5V is detected within a one-second or atwo-second window, or when the sum of X axis accelerometer data and Yaxis accelerometer data exceeds a threshold more than five times withinten seconds), or by another determination. Example rich data capturetriggers are described with reference to FIG. 7, below.

Monitoring the raw data for satisfaction of the rich data capturetrigger may involve evaluating the rich data capture trigger for a firstdata type. That is, the rich data capture trigger may detect aparticular signal feature in a particular data type, such asaccelerometer data, gyroscope data, vehicle speed data, enginetemperature data, or another data type. Further, the unsimplified blockof raw data 224 may comprise raw data of this first data type. That is,when the rich data capture trigger detects a particular signal featurein accelerometer data, the rich data capture trigger causes a block ofaccelerometer sensor data to be logged and transmitted to the telematicssystem.

Further, the unsimplified block of raw data 224 may also comprise rawdata of a second data type that is different from the first data type.The second data type may be complementary to the first data type in thatit may provide additional contextual information about the event thattriggered the satisfaction of the rich data capture trigger. Forexample, in the case of a rich data capture trigger that is designed tocapture information surrounding possible vehicle accidents orcollisions, the first data type may be a kind of vehicle kinematic data(e.g., accelerometer data or gyroscope data), which is likely to providethe strongest indicator of a collision, and the second data type mayinclude vehicle speed data or vehicle location data, which is likely toprovide useful contextual information surrounding the collision.

The unsimplified block of raw data 224 spans a data window that covers atime at which the rich data capture trigger was satisfied. The datawindow may be sufficiently large and of sufficient resolution to providesufficient contextual information surrounding the event that triggeredthe rich data capture trigger so that advanced data analysis techniques,such as machine learning techniques, may be applied to the unsimplifiedblock of raw data 224. In other words, advantageously, the unsimplifiedblock of raw data 224 contains raw data that is additional to the rawdata contained in the simplified set of raw data 222. That is, theunsimplified block of raw data 224 contains raw data that was discardedby the dataset simplification algorithm that was used to generate thesimplified set of raw data 222.

The unsimplified block of raw data 224 may capture raw data both beforeand after the time at which the rich data capture trigger is satisfied.When the unsimplified block of raw data 224 contains more than one typeof raw data, the data window for any of the types of raw data may bedifferent. In the example above regarding vehicle accident detection,the data window for vehicle accelerometer data may span about twoseconds (about 1 second on either side of the signal feature thatsatisfied the trigger), but the data window for vehicle location datamay span about ten seconds (about 5 seconds on either side of the signalfeature). The data window for the second type of raw data may bedifferent from the data window for the first type of raw data forhardware limitation reasons. For example, vehicle location data may onlyinclude data points that were gathered about every second, and thus, adata window that is larger than one second will capture significantlymore data points of location data than a data window spanning only onesecond. The data windows for data types that are collected at a higherrate (e.g., accelerometer data) may be smaller than data windows fordata types that are collected at a lower rate (e.g., vehicle locationdata) to ensure that adequate amounts of data of each data type arecaptured without capturing an unduly large amount of data. Otherexamples of data windows of different sizes are illustrated in FIG. 8,below.

Typically, the unsimplified block of raw data 224 may be an uneditedblock of all of the data points of the relevant data types that werecollected by the asset tracking device 200 throughout the relevant datawindows surrounding the event that led to the satisfaction of the richdata capture trigger. In some examples, the unsimplified block of rawdata 224 need not contain an entirely unedited block of raw data. It iscontemplated that the simplified block of raw data 224 may be reducedfrom the actual raw data collected by the asset tracking device 200, by,for example, various data smoothing, filtration, interpolation,averaging, or other data reduction means, provided that the unsimplifiedblock of raw data 224 is not simplified in the same manner as thesimplified set of raw data 222 and retains more resolution than thesimplified set of raw data 222.

Further, although the additional contextual data that is captured inaddition to the data type that triggers a rich data capture trigger maybe collected from raw data, in some examples, such additional contextualdata may be collected from data that has already been processed by adataset simplification algorithm. Thus, while the contextual data maynot necessarily provide additional raw data points, the contextual datamay be bundled together with the additional raw data collected by therich data capture trigger to provide additional context.

The asset tracking device 200 further includes a communication interface240 to transmit the simplified set of raw data 222 and the unsimplifiedblock of raw data 224 a server 204 of a telematics system, which may besimilar to the server 122 of the telematics system 120 of FIG. 1. Thecommunication interface 240 may include a cellular modem, such as anLTE-M modem, CAT-M modem, or other cellular modem configured forbidirectional communication via the network with which asset trackingdevice 200 may communicate with the server 204.

The unsimplified block of raw data 224 may be flagged (at any pointbetween logging and transmission) as being intended for separateprocessing from the simplified set of raw data, which will generally beused to support telematics services. Thus, the unsimplified block of rawdata 224 may be rerouted by the server 204 to an appropriate place fordata analysis (e.g., the rich data analysis module 126 of FIG. 1),without disrupting the telematics service with large quantities of richdata.

Further, each unsimplified block of raw data 224 may be labelledaccording to the particular rich data capture trigger used to capturethe data. For example, an unsimplified block of raw data 224 that wascaptured due to the detection of a disturbance in accelerometer datathat may be indicative of a vehicle collision, that unsimplified blockof raw data 224 may be labelled as potentially pertaining to a vehiclecollision. Similarly, an unsimplified block of raw data 224 that wascaptured due to the detection of a disturbance in accelerometer datathat may be indicative of the asset travelling over a pothole, thatunsimplified block of raw data 224 may be labelled as potentiallypertaining to a pothole incident. Thus, researchers may be able toanalyze the unsimplified blocks of raw data 224 and track the emergenceof such raw data more effectively.

Thus, the asset tracking device 200 may provide a telematics system withboth simplified data for a telematics service and rich data for morerigorous data analysis when particular signal features are detected inthe raw data.

FIG. 3 is a flowchart of an example method 300 for capturing data froman asset or asset tracking device. The method 300 may be understood tobe one example of how the asset tracking device 200 of FIG. 2 capturesraw data relating to an asset. Thus, for exemplary purposes, the method300 will be described with reference to the asset tracking device 200 ofFIG. 2. Further, the blocks of the method 300 are elaborated upon abovewith reference to the appropriate components of the asset trackingdevice 200 of FIG. 2. However, it is to be understood that the method300 may be applied by other asset tracking devices.

At block 302, the interface layer 210 of the asset tracking device 200obtains raw data from a data source onboard the asset 202. As describedabove, the data source may include a sensor, locating device, or onboarddiagnostic port.

At block 304, the controller 230 monitors the raw data for satisfactionof a simplified data capture trigger. The simplified data capturetrigger is included in the simplified data capture instructions 232. Asdescribed above, the simplified data capture trigger is a trigger thatdetermines when the raw data is to be evaluated for simplification andlogged for transmission to a telematics system.

At block 306, when the simplified data capture trigger is satisfied, thecontroller 230 performs a dataset simplification algorithm on the rawdata to generate the simplified set of raw data 222, and at block 308,logs the simplified set of raw data 222 in memory 220. As describedabove, the dataset simplification algorithm determines which data pointsshould be recorded for transmission to the telematics system and whichdata points should be discarded.

At block 310, the controller 230 monitors the raw data for satisfactionof a rich data capture trigger. The rich data capture trigger isincluded in the rich data capture instructions 234. Monitoring of theraw data for the rich data capture trigger may take place in parallelwith monitoring the raw data for the simplified data capture trigger. Asdescribed above, the rich data capture trigger is a trigger that detectsa feature of the raw data that warrants further analysis, and causes ablock of raw data that captures details surrounding the event to bestored and transmitted to the telematics system.

At block 312, when the rich data capture trigger is satisfied, thecontroller 230 identifies the unsimplified block of raw data 224 in theraw data for rich data analysis and, at block 314, logs the unsimplifiedblock of raw data 224 in memory 220. As described above, theunsimplified block of raw data 224 spans a data window that covers atime at which the rich data capture trigger was satisfied, and mayinclude one or more data types spanning one or more data windows.

At block 316, the communication interface 240 transmits the simplifiedset of raw data 222 and the unsimplified block of raw data 224 to theserver 204. As described above, these data may be flagged and/ortransmitted separately or together according to any program thatcontrols the transmission of data from the asset tracking device 200 tothe server 204, and may be used in a telematics service or for rich dataanalysis, as appropriate.

The method 300 may be embodied in instructions (such as the simplifieddata capture instructions 232 and rich data capture instructions 234)stored on a non-transitory machine-readable storage medium that isexecutable by the controller 230 to perform the method 300. Thenon-transitory machine-readable storage medium may include ROM, RAM,flash memory, magnetic storage, optical storage, and similar, or anycombination thereof, for storing instructions and data as discussedherein.

Thus, a non-transitory machine-readable storage medium may containinstructions that when executed cause the controller 230 to obtain rawdata from a data source onboard the asset 202 and monitor the raw datafor satisfaction of a simplified data capture trigger. When thesimplified data capture trigger is satisfied, the instructions may causethe controller 230 to perform a dataset simplification algorithm on theraw data to generate the simplified set of raw data 222 and log thesimplified set of raw data 222. The instructions may further cause thecontroller 230 to monitor the raw data for satisfaction of a rich datacapture trigger. When the rich data capture trigger is satisfied, theinstructions may cause the controller 230 to identify the unsimplifiedblock of raw data 224 in the raw data for rich data analysis, log theunsimplified block of raw data 224, and transmit the simplified set ofraw data 222 and the unsimplified block of raw data 224 to a server. Theunsimplified block of raw data 224 may span a data window that covers atime at which the rich data capture trigger was satisfied. Theunsimplified block of raw data 224 may contain raw data that isadditional to the raw data contained in the simplified set of raw data.

FIG. 4A is a data plot 400A displaying example raw data 402 collected atan asset or asset tracking device. The raw data 402 may be understood tobe one example of the raw data collected by the asset tracking device200 of FIG. 2. The raw data may include any data collected from a datasource onboard an asset. For example, the raw data 402 may be acomposite of XY plane accelerometer data collected from an accelerometerof the asset tracking device. The raw data 402 is shown in a smoothsolid line to indicate that the raw data 402 is of high resolution. Thedata plot 400A is shown with arbitrary units of magnitude along the Yaxis and arbitrary units of time along the X axis for exemplary purposesonly.

FIG. 4B is a data plot 400B displaying an example simplified set of rawdata 410 derived from the application of a dataset simplificationalgorithm to the raw data 402 of FIG. 4A. The simplified set of raw data410 contains far fewer data points than the raw data 402 itself. Thesimplified set of raw data 410 is shown as a set of circular data points412. Dashed lines between the data points 412 indicate interpolatedvalues where no data points are stored between the data points 412. Thedata plot 400B is shown with arbitrary units of magnitude along the Yaxis and arbitrary units of time along the X axis for exemplary purposesonly.

FIG. 4C is a data plot 400C displaying example unsimplified blocks ofraw data 420, 422 derived from the application of a raw data capturealgorithm to the raw data of 402 FIG. 4A. The unsimplified blocks of rawdata 420, 422 may be understood to be examples of the unsimplified blockof raw data 224 captured by the asset tracking device 200 of FIG. 2. Theunsimplified blocks of raw data 420, 422 span rich data windows 424,426, respectively. The unsimplified blocks of raw data 420, 422 may beunderstood to be snippets of the raw data 402 covered by the rich datawindows 424, 426. As can be seen by comparison to the simplified set ofraw data 410 of FIG. 4B, the unsimplified blocks of raw data 420, 422contain significantly more data points than the simplified set of rawdata 410, which may be particularly useful for rich data analysis, suchas machine learning.

FIG. 5 is a data plot 500 displaying an example hybridized set of rawdata 502 that contains the simplified set of raw data 410 of FIG. 4B andthe unsimplified blocks of raw data 420, 422 of FIG. 4C. The hybridizedset of raw data 502 contains small amounts of data throughout itsduration that would be sufficiently detailed to support a telematicsservice (the simplified set of raw data 410), in addition to highlydetailed snippets of raw data for rich data analysis that providedetailed descriptions of particularly interesting events that occur inthe raw data (the unsimplified blocks of raw data 420, 422). Thehybridized set of raw data 502 illustrates how the techniques describedherein may be applied to enable an asset tracking device to capture rawdata in an efficient matter during a majority of its operation whilecollecting short high-density snippets of data to describe interestingevents detected in the raw data.

FIG. 6 is a block diagram of another example asset tracking device 600that captures simplified data and rich data. The asset tracking device600 is similar to the asset tracking device 200 of FIG. 2, withcomponents numbered in the “600” series rather than the “200” series.Thus, the asset tracking device 600 is located onboard an asset 602, andincludes an interface layer 610, a logging memory 620 containing asimplified set of raw data 622 and unsimplified block of raw data 624, acontroller 630 to execute simplified data capture instructions 632 andrich data capture instructions 634, and a communication interface 640 tocommunicate with a server 604. For further description of thesecomponents, reference may be had to the like components in thedescription of the asset tracking device 200 of FIG. 2.

In the present example, the asset 602 includes a vehicle, such as atransport truck or passenger vehicle, that features an onboarddiagnostic port 603. The onboard diagnostic port 603 provides access toasset data (e.g., vehicle information data) that can be obtained by aninterface of the interface layer 610. Thus, the interface layer 610 isable to gather engine speed data, battery voltage, fuel level, and otherdata made available through the onboard diagnostic port. Further, theasset tracking device includes a sensor 614 to gather sensor data at theasset tracking device 600. The sensor 614 may include a kinematic sensor(e.g., an accelerometer or gyroscope), magnetometer, temperature sensor,or another type of sensor that can be obtained by an interface of theinterface layer 610. The asset tracking device 600 may include multiplesensors 614. The asset tracking device 600 further includes a locatingdevice 616 to obtain location data of the asset tracking device 600. Thelocating device 616 may include a GPS module, GNSS module (e.g., anU-BLOX ZOE M8G), or other interface to obtain a location from a locatingsystem and that can be obtained by an interface of the interface layer610. The asset tracking device 600 may include multiple locating devices616. Any of the onboard diagnostic port 603, sensor 614, and locatingdevice 616 may be referred to as a data source.

The interface layer 610 may receive raw data from the sensor 614,locating device 616, or the onboard diagnostic port 603. The assettracking device 600 further includes a raw data buffer 612 to buffersuch raw data received from the interface layer 610. The raw data buffer612 provides temporary memory storage for the raw data before it islogged to the logging memory 620. When the controller 630 executessimplified data capture instructions 632 and rich data captureinstructions 634, the controller 630 may monitor the raw data in the rawdata buffer 612 for satisfaction of a simplified dataset logging triggeror a rich data capture trigger. Thus, raw data flows from one or more ofthe onboard diagnostic port 603, sensor 614, and locating device 616,through to the interface layer 610, and stored temporarily on the rawdata buffer 612, after which a portion of the raw data is logged inlogging memory 620 (as a simplified set of raw data 622 or anunsimplified block of raw data 624), prior to transmission by thecommunication interface 640 to the server 604.

The size of the data window that is spanned by the unsimplified block ofraw data 624 may be determined in part by a characteristic of the rawdata buffer 612, such as its size or refresh rate. In particular, themaximum amount of data that is included in the data window prior to theincident that satisfies the rich data capture trigger may be determinedby the amount of raw data of the relevant data type that is stored inthe raw data buffer 612 before the raw data buffer 612 is overwritten(as any earlier data may have been overwritten), but the maximum amountof data that is included in the data window after the incident may notbe so limited. For example, if the raw data buffer 612 is capable ofstoring 1000 ms of accelerometer data before accelerometer data becomesoverwritten, the data window for accelerometer data in any unsimplifiedblock of raw data 624 may include data up to 1000 ms prior tosatisfaction of the rich data capture trigger, and may include 1000 msor more of accelerometer data after satisfaction of the rich datacapture trigger. As will be seen below (e.g., in FIG. 11), the size ofthe data window after the satisfaction of the rich data capture triggermay be further configurable.

FIG. 7 is a block diagram of example non-transitory machine-readablestorage medium 700 that contains simplified data capture instructions710 and rich data capture instructions 750. The simplified data captureinstructions 710 may be understood to be one example of the simplifieddata capture instructions 632 of FIG. 6, and the rich data captureinstructions 750 may be understood to be one exampled of the rich datacapture instructions 634 of FIG. 6, each of which may be stored onmemory of the controller 630. Thus, for convenience, description of theinstructions 710 and instructions 750 will be made with reference to theasset tracking device 600 of FIG. 6, but this is not limiting, and theinstructions 710, 750 may be performed by other systems and/or devices.

The simplified data capture instructions 710 contains simplified datacapture triggers 712, 714, 716, and 718, each of which cause thecontroller 630 to log a simplified set of raw data 622 when obtainmentof the raw data results in satisfaction of a simplified data capturetrigger, such as when a particular signal feature in the raw data isdetected or when a particular operating condition of the asset trackingdevice 600 is met. It is emphasized that the simplified data captureinstructions 710 shown are for exemplary purposes only, and thesimplified data capture instructions 710 may contain other or additionalsimplified data capture triggers.

For example, the buffer fill trigger 712 may cause the controller 630 tolog a simplified set of raw data 622 when the raw data buffer 612becomes full of either a particular data type or as a whole. When theraw data buffer 612 becomes full, the controller 630 may perform adataset simplification algorithm on the data present in the raw databuffer 612 and store the resulting simplified dataset in the memory 220prior to the raw data buffer 612 being cleared or overwritten. Thus,data may be logged in accordance with a hardware limitation of the assettracking device 200.

As another example, the timeout trigger 714 may cause the controller 630to log a simplified set of raw data 622 when a timeout value is reached.When no simplified set of raw data 622 has been logged within aparticular time (e.g., 100 seconds), the controller 630 may perform adataset simplification algorithm on the data present in the raw databuffer 612 and store the resulting simplified dataset in the loggingmemory 620. Thus, a baseline frequency for data logging may bemaintained.

As another example, the start-stop trigger 716 may cause the controller630 to log a simplified set of raw data 622 when the asset 602 isdetermined to have come to a stop or has started moving from a stop.When the asset 602 is determined to have come to a stop or have startedmoving from a stop, which may have been determined by an analysis oflocation data obtained by the locating device 616, the controller 630may perform a dataset simplification algorithm on the data present inthe raw data buffer 612 and store the resulting simplified dataset inthe logging memory 620. Thus, it may be ensured that data pertaining tocritical points in the travel of the asset 202, which may include startsand stops, are logged.

As another example, the location discrepancy trigger 718 may cause thecontroller 630 to log a simplified set of raw data 622 when the measuredlocation of the asset tracking device 200 is determined to differexcessively from a predicted position of the asset tracking device 200.That is, the asset tracking device 200 may periodically predict itsfuture position, and when location data obtained by the locating device616 indicates that the asset tracking device 200 is distant from thatfuture position by a particular threshold value, the controller 630 mayperform a dataset simplification algorithm on the data present in theraw data buffer 612 and store the resulting simplified dataset in thelogging memory 620.

Again, it is emphasized that the simplified data capture instructions710 shown are for exemplary purposes only, and the simplified datacapture instructions 710 may contain additional simplified data capturetriggers, including triggers which may be satisfied by criteriapertaining to other data types in the raw data or other operatingconditions of the asset tracking device 200.

Similarly, the rich data capture instructions 750 contains rich datacapture triggers 752, 754, and 756, each of which cause the controller630 to log an unsimplified block of raw data 624 when certain criteriaare met. It is emphasized that the rich data capture instructions 750shown are for exemplary purposes only, and the rich data captureinstructions 750 may contain other or additional rich data capturetriggers.

For example, the XY accelerometer trigger 752 may cause the controller630 to log an unsimplified block of raw data 624 when a composite ofaccelerometer data in the X direction and accelerometer data in the Ydirection exceeds a threshold value (e.g., 2.5 g). That is, the sensor614 includes an accelerometer, and when the controller 630 detects adisturbance in the XY plane that surpasses a threshold value, thecontroller 630 causes an unsimplified block of raw data 624 to be loggedto the logging memory 620.

The XY accelerometer trigger 752 may be employed for the detection andanalysis of incidents in which the asset 602 (e.g., a vehicle) isinvolved in a vehicle collision or other minor damage and impact-relatedevent. The unsimplified block of raw data 624 that is logged may containaccelerometer data in the X and Y directions, and may further containaccelerometer data in the Z direction, engine speed data collectedthrough the onboard diagnostic port 603, location data collected fromthe locating device 616, or any other data that may assist in theanalysis of a vehicle collision or other impact-related event. Thus,data collected from the XY accelerometer trigger 752 may be used invehicle collision reconstruction, vehicle impact analysis, and otherforms of analysis. Such analyses may be particularly benefited by therich set of data provided by the unsimplified block of raw data 624,which may enable advanced forms of analytics, including machine learningtechniques.

As another example, the Z accelerometer trigger 754 may cause thecontroller 630 to log an unsimplified block of raw data 624 whenaccelerometer data in the Z direction exceeds a threshold value. Thatis, the sensor 614 includes an accelerometer, and when the controller630 detects a disturbance in the Z direction that surpasses a thresholdvalue, the controller 630 causes an unsimplified block of raw data 624to be logged to the logging memory 620.

The Z accelerometer trigger 754 may be employed for the detection andanalysis of incidents in which the asset 602 (e.g., a vehicle) isinvolved in travelling over a pothole, speedbump, or other abnormalsurface. The unsimplified block of raw data 624 that is logged maycontain accelerometer data in the Z direction, and may further containaccelerometer data in the X and Y directions, engine speed datacollected through the onboard diagnostic port 603 location datacollected from the locating device 616, or any other data that mayassist in the analysis of an event in which the asset 602 travels over apothole, speedbump, or other abnormal surface.

As another example, the magnetometer discrepancy trigger 756 may causethe controller 630 to log an unsimplified block of raw data 624 when amagnetometer reading differs from a gyroscopic reading. That is, theasset tracking device 600 may include a gyroscope (a sensor 614) and amagnetometer (another sensor 614) to calibrate the yaw dimensionmeasured by the gyroscope, and when the controller 630 detects adiscrepancy between the magnetometer and the gyroscope that exceeds athreshold value, the controller 630 causes an unsimplified block of rawdata 624 to be logged to the logging memory 620. The unsimplified blockof raw data 624 that is logged may contain magnetometer data andgyroscope data.

Again, it is emphasized that the rich data capture instructions 750shown are for exemplary purposes only, and the rich data captureinstructions 750 may contain additional rich data capture triggers,including triggers which may be satisfied by criteria pertaining toother data types in the raw data or other operating conditions of theasset tracking device 200.

FIG. 8 is a data plot 800 that displays a hybridized set of raw data 800that is similar to the hybridized set of raw data 502 of FIG. 5, withelements numbered in the “800” series rather than the “500” series.Thus, the hybridized set of raw data 800 includes a simplified set ofraw data 810 and unsimplified blocks of raw data 820, 822.

However, the unsimplified blocks of raw data 820, 822 contain raw dataof different data types spanning differently sized rich data windows824, 826, and 828, 830, respectively. These unsimplified blocks of rawdata 820, 822 may have been generated when the satisfaction of a richdata capture trigger caused additional contextual data of a differentdata type than the data type evaluated for satisfaction of the rich datacapture trigger to be logged.

For example, the unsimplified block of raw data 820 may have been loggedupon satisfaction of the XY accelerometer trigger 752 of FIG. 7, and theunsimplified block of raw data 820 may include XY accelerometer data (afirst data type) spanning the rich data window 826, and may furthercontain vehicle location data (a second data type) spanning the richdata window 824. The rich data window 826 may be a more narrow window ofhighly dense data, whereas the rich data window 824 may be a broaderwindow of less dense data. That is, the XY accelerometer data may becollected at a higher frequency than the vehicle location data, and thusthe vehicle location data may be collected over a broader data window toensure that an adequate number of location points are logged to providesufficient context around the incident. For example, the XYaccelerometer data may be collected at a frequency of about 100 Hz (onehundred times per second), and its data window may span about twoseconds in length, whereas the vehicle location data may be collected ata frequency of about 1 Hz (once per second), and its data window mayspan about ten seconds in length. The rich data window 824 spanned bythe vehicle location data may be referred to as a supplementary datawindow because it provides supplementary data to the data type that wasevaluated for satisfaction of the rich data capture trigger.

FIG. 9 is a schematic diagram of another example system 900 forcapturing data from assets or asset tracking devices. The system 900 issimilar to the system 100 of FIG. 1, and thus includes an asset trackingdevice 910 onboard an asset 902 to obtain raw data 904 from a datasource onboard the asset 902. Further, the asset tracking device 910monitors the raw data 904 for satisfaction of a simplified data capturetrigger, and when the simplified data capture trigger is satisfied,performs a dataset simplification algorithm on the raw data 904 togenerate a simplified set of raw data 914 and log the simplified set ofraw data 914. Further, the asset tracking device 910 monitors the rawdata 904 for satisfaction of a rich data capture trigger, and when therich data capture trigger is satisfied, identifies an unsimplified blockof raw data 916 in the raw data 904 for rich data analysis and logs theunsimplified block of raw data 916. The asset tracking device 910transmits the simplified set of raw data 914 and the unsimplified blockof raw data 916, shown as transmitted data 912, to a telematics system920, which includes the server 922. The server 922 runs a telematicsservices module 924 and a rich data analysis module 926. For furtherdescription of the above components, the system 100 of FIG. 1 may bereferenced.

However, in the system 900, the server 922 provides a data capturetrigger configuration module 928 to configure a rich data capturetrigger, which may be included in data capture instructions 930 andtransmitted to the asset tracking device 910. The rich data capturetrigger defines when a controller of the asset tracking device 910onboard the asset 902 is to identify and log an unsimplified block ofraw data 916 for rich data analysis.

The data capture instructions 930 may contain a complete set ofinstructions to cause the asset tracking device 910 to capture the rawdata 904 according to a dataset simplification algorithm (such as, as,for example, in the simplified data capture instructions 232 of FIG. 2.)and a rich data capture algorithm (such as, for example, in the richdata capture instructions 234 of FIG. 2), or may be in the form ofmerely an update to existing instructions onboard the asset trackingdevice 910 in which the asset tracking device 910 is configured with anew rich data capture trigger. In either case, the data captureinstructions 930 contain a rich data capture trigger obtained by thedata capture trigger configuration module 928.

The data capture trigger configuration module 928 obtains, whetherthrough selection from a database or through generation via a userinterface, a rich data capture trigger. The data capture triggerconfiguration module 928 may provide a user interface, accessible by auser with access to the telematics system 920, to configure the richdata capture trigger. An example of such a user interface is shown inFIG. 11, below.

Thus, the server 922 obtains the rich data capture trigger, transmitsdata capture instructions 930 to the asset tracking device 910, and,following data capture onboard the asset tracking device 910, receivesthe simplified set of raw data 914 and the unsimplified block of rawdata 916 from the asset tracking device 910.

FIG. 10 is a flowchart of an example method 1000 for capturing data froman asset or asset tracking device. The method 1000 involves transmissionof a rich data capture trigger to the asset tracking device. The method1000 may be understood to be one example of a method by which the server922 configures the asset tracking device 910 with data captureinstructions 930 that contain the rich data capture trigger, and obtainsthe simplified set of raw data 914 and unsimplified block of raw data916 from the asset tracking device 910. However, this is not limiting,it is to be understood that the method 1000 may be performed by othersystems and/or devices.

At block 1002, the server 922 obtains a rich data capture trigger thatdefines when a controller of the asset tracking device 910 onboard anasset 902 is to identify the unsimplified block of raw data 916 in rawdata 904 on the asset tracking device 910 for rich data analysis. Theraw data 904 is obtained by the asset tracking device 910 from a datasource onboard the asset 902.

At block 1004, the server 922 transmits data capture instructions 930 tothe asset tracking device 910. As described above, the data captureinstructions 930 may contain a complete set of instructions or merely anupdate to instructions for the asset tracking device 910.

The data capture instructions 930 cause a controller of the assettracking device 910 to monitor the raw data 904 for satisfaction of asimplified data capture trigger. When the simplified data capturetrigger is satisfied, the controller of the asset tracking device 910performs a dataset simplification algorithm on the raw data 904 togenerate the simplified set of raw data 914, and logs the simplified setof raw data 914. The data capture instructions 930 further cause thecontroller to monitor the raw data 904 for satisfaction of a rich datacapture trigger, and when the rich data capture trigger is satisfied,identify the unsimplified block of raw data 916 in the raw data 904 forrich data analysis and log the unsimplified block of raw data 916. Theunsimplified block of raw data 916 spans a data window that covers atime at which the rich data capture trigger was satisfied. Theunsimplified block of raw data 916 contains raw data that is additionalto the raw data contained in the simplified set of raw data 914.

Following data capture onboard the asset tracking device 910, at block1006, the server 922 receives the simplified set of raw data 914 and theunsimplified block of raw data 916 from the asset tracking device 910.

The method 1000 may involve the server 922 providing a user interface toconfigure the rich data capture trigger and/or the data window so thatthe rich data capture trigger may be obtained by configuration throughthe user interface. The data capture instructions 930 may cause acontroller of the asset tracking device 910 to, as discussed above,evaluate a rich data capture trigger with respect to one or more datatypes, which may involve determining whether a value or a compositevalue of such data types surpass a threshold values, and capturerelevant raw data across one or more data windows that may be ofdifferent duration. The user interface provided by the server 922 mayenable the configuration of any of such data types, threshold values,data windows, or any other aspect of such rich data capture triggers.

The method 1000 may involve the technical infrastructure of thetelematics system 920, as represented by the server 922, flagging theunsimplified block of raw data 916 for separate treatment from thesimplified set of raw data 914. Further, the method 1000 may furtherinvolve the server 922 processing the simplified set of raw data 914 fortelematics services via the telematics services module 924, andperforming rich data analysis on the unsimplified block of raw data 916via the rich data analysis module 926.

The method 1000 may be embodied in instructions, which may be termeddata capture control instructions, stored on a non-transitorymachine-readable storage medium that is executable by a processor of theserver 922 to perform the method 1000. The non-transitorymachine-readable storage medium may include read-only memory (ROM),random-access memory (RAM), flash memory, magnetic storage, opticalstorage, and similar, or any combination thereof, for storinginstructions and data as discussed herein.

FIG. 11 is a schematic diagram of an example user interface 1100 toconfigure a rich data capture trigger for execution at an asset or assettracking device. The user interface 1100 may be understood to be oneexample of a user interface provided by the rich data captureconfiguration module 928 of FIG. 9 for the configuration of a rich datacapture trigger of the data capture instructions 930. However, this isnot limiting, it is to be understood that the user interface 1100 may beemployed by other systems and/or devices.

The user interface 1100 includes a trigger selection component 1102 toenable a user to select one or more rich data capture triggers forconfiguration. The user interface 1100 further includes a rich datacapture trigger generation component 1103 to add a new rich data capturetrigger to the trigger selection component 1102. The trigger selectioncomponent 1102 enables a user to select which rich data capturetriggers, of a list of available triggers (e.g., the “XY AccelerometerThreshold” trigger, “Z Accelerometer Threshold” trigger, and “Engine RPMVariance” trigger, as shown), are enabled for a particular assettracking device or group of asset tracking devices. The triggerselection component 1102 includes, for each rich data capture trigger,an “ON” button to enable the rich data capture trigger on the selecteddevices, an “OFF” button to disable the rich data capture trigger on theselected devices, and an “EDIT” button to configure a particular richdata capture trigger.

The user interface 1100 further includes a device selection component1104 to enable a user to select one or more asset tracking devices orgroups of asset tracking devices for configuration of the rich datacapture triggers thereof. That is, a user may select one or more assettracking devices (e.g., the “TEST GROUP” as shown) in the deviceselection component 1104, and use the trigger selection component 1102to determine which rich data capture triggers are enabled for theselected devices.

The groups of asset tracking devices may be categorized according tocharacteristics of the assets being tracked by those asset trackingdevices. For example, asset tracking devices may be categorizedaccording to the vehicle type being tracked (e.g., “HEAVY TRUCKS” and“PASSENGER VEHICLES”). Different categories of assets may be of interestfor different types of rich data analyses. For example, a researcher maybe particularly interested in studying incidents of heavy truckstravelling over potholes, and thus may select the “HEAVY TRUCKS”grouping under the device selection component 1104 and enable the “ZAccelerometer Threshold” trigger under the trigger selection component1102 so that all asset tracking devices in the “HEAVY TRUCKS” group willtransmit rich blocks of raw data relating to trucks travelling overpotholes. As another example, a researcher may select the “PASSENGERVEHICLES” grouping under the device selection component 1104 and enablethe “XY Accelerometer Threshold” trigger under the trigger selectioncomponent 1102 so that all asset tracking devices in the “PASSENGERVEHICLES” grouping will transmit rich blocks of raw data relating topossible vehicle collisions and other impact events. Thus, a research isable to push different rich data capture triggers to different groups ofasset tracking devices tracking different types of assets for desiredpurposes.

The user interface 1100 further includes a trigger parameterconfiguration component 1106 to enable a user to configure any aspect ofa rich data capture trigger, including of any data type involved inevaluation of the trigger, any threshold value involved in theevaluation of the trigger, any data window, or any other aspect of arich data capture trigger. For exemplary purposes, the trigger parameterconfiguration component 1106 is shown for example as a text box thatenables text configuration of the parameters of a rich data capturetrigger. Thus, it may be seen that the “XY Accelerometer Threshold”trigger may be configured with respect to the trigger description (“XYAccelerometer Threshold”), trigger evaluation type (“Threshold”),threshold value (“2500 mg”), data window size pre-trigger (“1000 ms”),data window size post-trigger (“1000 ms”), evaluated data types (“XAccelerometer”, “Y Accelerometer”, “Z Accelerometer”), collected datatypes (“X Accelerometer”, “Y Accelerometer”, “Z Accelerometer”, “EngineSpeed”, “GPS Location”, and the enabled/disabled status of the triggerfor the selected devices (“true”).

In other examples, additional trigger parameters may be configured. Forexample, a trigger parameter may include a maximum number of triggeringevents that are permitted to cause the rich data capture trigger tocollect rich data within a given timeframe so that any given rich datatrigger may be restricted from collecting unduly large amounts of data.As another example, a trigger parameter may include logic that dictatesthat the data window for a rich data capture trigger may be extendedwhen the same rich data capture trigger is satisfied multiple timeswithin a short time period. Thus, rather than several separateunsimplified blocks of raw data being collected one after the other(overlapping), a single contiguous unsimplified block of raw data may becollected to cover multiple instances of the same rich data capturetrigger being satisfied within a short time period. For example, if theXY Accelerometer Threshold trigger were satisfied at 5 seconds, 5.9seconds, and 6.5 seconds, rather than collecting three separate blocksof data from 4 seconds to 6 seconds, from 4.9 seconds to 6.9 seconds,and from 5.5 seconds to 7.5 seconds, the data window of the firstinstance of the satisfaction of the trigger may be extended to be from 4seconds to 7.5 seconds, thereby covering all instances of satisfactionof the trigger within this time period as one contiguous block of data.A timestamp for each instance at which the rich data capture trigger wassatisfied may be recorded in metadata. The XY Accelerometer ThresholdTrigger may be configured in this way with parameters such as, forexample, “Data Window Extendable=‘Yes’”, “Data Window ExtensionRange=‘2000 ms’”, and “Data Window Maximum Size=10000 ms”, to enable therich data capture trigger to extend the length of its data window, postsatisfaction of the trigger, if that trigger is satisfied again within2000 milliseconds of it being initially satisfied. The data window maybe extended on a rolling basis with each instance of the trigger beingsatisfied, and thus the data window may be extended indefinitely untilthe trigger is not satisfied within the data window extension range ofthe last instance of its satisfaction, or until another threshold ismet, such as a maximum size of the data window (e.g., 10,000 ms).

Different rich data capture triggers may collect the same types of data.For example, the XY Accelerometer Threshold trigger, when satisfied by asignal feature detected X and/or Y accelerometer data, may trigger thecollection of X, Y, and Z accelerometer data. Similarly, the ZAccelerometer Threshold trigger, when satisfied by a signal feature in Zaccelerometer data, may trigger the collection of X, Y, and Zaccelerometer data. If the XY Accelerometer Threshold trigger and the ZAccelerometer Threshold were both triggered within the same time period,duplicate accelerometer data may be collected. However, in someexamples, only one instance of the accelerometer data may be transferredfrom the raw data buffer to the logging memory, and metadata mayindicate which portions of the accelerometer data pertain to thesatisfaction of which trigger, thereby avoiding the saving andtransmission of duplicate data. Some of such metadata may indicate thata particular point of accelerometer data was saved as pertaining to thesatisfaction of two (or more) triggers. For example, a particular pointof accelerometer data may be indicated as having been saved due tosatisfaction of both the XY Accelerometer Threshold trigger and the ZAccelerometer Threshold trigger.

The user interface 1100 further includes an instruction transmissioncomponent 1108 to transmit data capture instructions to the selectedasset tracking devices to configure the selected asset tracking devicesto monitor raw data for the selected rich data capture triggers. Thedata capture instructions may be transmitted in the form of an update tothe data capture instructions onboard the asset tracking devices (e.g.,a firmware update, or in the form of a communication that merelyinstructs the asset tracking devices to enable or disable one or morerich data capture triggers which the asset tracking devices are alreadyenabled to perform.

Thus, a telematics system may remain efficient in its collection ofsimplified data to support its telematics services without missingopportunities for more rigorous data analysis. Asset tracking devicesmay be configured to run rich data capture instructions in which rawdata collected by the asset tracking device is evaluated for particularsignal features that are indicative of events that warrant furtheranalysis. These rich data capture instructions may be configuredremotely and pushed to an individual asset tracking device for ease oftesting and experimentation without impact to existing data collectiontechniques running on the asset tracking device.

The above disclosure describes that a rich data capture algorithm is tobe applied on an asset tracking device in parallel with a datasetsimplification algorithm so as to provide data for both a telematicsservice and for rich data analysis. However, it is contemplated that, insome examples, raw data may be captured from an asset tracking devicefor rich data analysis without the capture of simplified sets of rawdata for a telematics services, as shown for example in FIG. 12 and FIG.13, below. An asset tracking device may be configured in such a way ifit is to be used primarily for the purpose of rich data collection,testing, experimentation, the study of vehicular operation and vehiculartravel conditions, and the like.

FIG. 12 is a block diagram of another example asset tracking device 1200that captures rich data. The asset tracking device 1200 is similar tothe asset tracking device 200 of FIG. 2, and therefore includes aninterface layer 1210 to obtain raw data from a data source onboard anasset 1202, a memory 1220 to store the raw data, a controller 1230 toexecute rich data capture instructions 1234, and a communicationinterface 1240. For further description of these components, thedescription of the asset tracking device 200 of FIG. 2 may bereferenced.

The rich data capture instructions 1234 monitor the raw data forsatisfaction of a rich data capture trigger. When the rich data capturetrigger is satisfied, the controller 1230 identifies a rich block of rawdata 1224 in the raw data for rich data analysis and logs the rich blockof raw data. The rich block of raw data 1224 spans a data window thatcovers a time at which the rich data capture trigger was satisfied.

The communication interface 1240 transmits the rich block of raw data1224 to a server 1204 for analysis.

FIG. 13 is a flowchart of another example method 1300 for capturing datafrom an asset or asset tracking device. The method 1300 may beunderstood to be one example of how the asset tracking device 1200 ofFIG. 12 captures raw data relating to an asset. Thus, for exemplarypurposes, the method 1300 will be described with reference to the assettracking device 1200 of FIG. 2. However, it is to be understood that themethod 300 may be applied by other asset tracking devices. Further, themethod 1300 may be similar to the method 300 of FIG. 3, and thereforefor further description of the blocks of the method 1300, the blocks ofthe method 300 may be referenced.

At block 1302, the interface layer 1210 of the asset tracking device1200 obtains raw data from a data source onboard the asset 1202. Atblock 1304, the controller 1230 monitors the raw data for satisfactionof a rich data capture trigger. When the rich data capture trigger issatisfied, at block 1306, the controller 1230 identifies a rich block ofraw data 1224 in the raw data for rich data analysis and logs the richblock of raw data in memory 1220 at block 1308. The rich block of rawdata 1224 spans a data window that covers a time at which the rich datacapture trigger was satisfied. At block 1310, the communicationinterface 1240 transmits the rich block of raw data 1224 to the server1204.

The method 1300 may be embodied in instructions stored on anon-transitory machine-readable storage medium that is executable by thecontroller 1230 to perform the method 1300. The non-transitorymachine-readable storage medium may include read-only memory (ROM),random-access memory (RAM), flash memory, magnetic storage, opticalstorage, and similar, or any combination thereof, for storinginstructions and data as discussed herein.

It should be recognized that features and aspects of the variousexamples provided above can be combined into further examples that alsofall within the scope of the present disclosure. The scope of the claimsshould not be limited by the above examples but should be given thebroadest interpretation consistent with the description as a whole.

1. A method comprising: obtaining raw data from a data source onboard anasset; monitoring the raw data for satisfaction of a simplified datacapture trigger; when the simplified data capture trigger is satisfied,performing a dataset simplification algorithm on the raw data togenerate a simplified set of raw data, and logging the simplified set ofraw data; monitoring the raw data for satisfaction of a rich datacapture trigger; when the rich data capture trigger is satisfied,identifying and logging an unsimplified block of raw data for rich dataanalysis, the unsimplified block of raw data spanning a data window thatcovers a time at which the rich data capture trigger was satisfied, theunsimplified block of raw data containing raw data that is additional tothe raw data contained in the simplified set of raw data; andtransmitting the simplified set of raw data and the unsimplified blockof raw data to a server.
 2. The method of claim 1, wherein: monitoringthe raw data for satisfaction of the rich data capture trigger comprisesevaluating the rich data capture trigger for a first data type; and theunsimplified block of raw data comprises raw data of the first datatype.
 3. The method of claim 2, wherein evaluation of the rich datacapture trigger comprises one or more of: determining whether a value ofa data point in the raw data of the first data type surpasses a firstthreshold value; and determining whether a composite value of a group ofdata points in the raw data of the first data type that spans anevaluation window surpasses a second threshold value.
 4. The method ofclaim 2, wherein the unsimplified block of raw data further comprisesraw data of a second data type different from the first data type. 5.The method of claim 4, wherein the raw data of the second data typespans a supplementary data window that is greater in duration than thedata window that is spanned by the raw data of the first data type. 6.The method of claim 4, wherein the asset comprises a vehicle, the firstdata type comprises vehicle accelerometer data, and wherein the seconddata type comprises vehicle speed data or vehicle location data.
 7. Themethod of claim 1, wherein the simplified set of raw data is to beprocessed for telematics services, and wherein the method furthercomprises flagging the unsimplified block of raw data for rich dataanalysis separate from processing of the simplified set of raw data forthe telematics services.
 8. The method of claim 7, wherein the rich dataanalysis comprises machine learning analysis.
 9. The method of claim 1,wherein the data source comprises one or more of: an onboard diagnosticport of the asset; a locating device of the asset; a locating device ofan asset tracking device onboard the asset; a sensor of the asset; and asensor of an asset tracking device onboard the asset.
 10. The method ofclaim 1, further comprising buffering the raw data in a raw data bufferwhere the raw data is monitored for satisfaction of the simplified datacapture trigger and the rich data capture trigger.
 11. The method ofclaim 1, wherein the dataset simplification algorithm comprises a linesimplification algorithm that reduces a curve of raw data composed ofline segments into a similar curve with fewer points.
 12. An assettracking device comprising: an interface layer to obtain raw data from adata source onboard an asset; a memory to store the raw data; acontroller to execute simplified data capture instructions to: monitorthe raw data for satisfaction of a simplified data capture trigger; andwhen the simplified data capture trigger is satisfied, perform a datasetsimplification algorithm on the raw data to generate a simplified set ofraw data and log the simplified set of raw data; the controller furtherto execute rich data capture instructions to: monitor the raw data forsatisfaction of a rich data capture trigger; and when the rich datacapture trigger is satisfied, identify and log an unsimplified block ofraw data for rich data analysis, the unsimplified block of raw dataspanning a data window that covers a time at which the rich data capturetrigger was satisfied, the unsimplified block of raw data containing rawdata that is additional to the raw data contained in the simplified setof raw data; and a communication interface to transmit the simplifiedset of raw data and the unsimplified block of raw data to a server. 13.The asset tracking device of claim 12, further comprising a raw databuffer to store the raw data to be monitored for satisfaction of thesimplified data capture trigger and the rich data capture trigger. 14.The asset tracking device of claim 12, further comprising logging memoryto store the logged simplified set of raw data and the loggedunsimplified block of raw data prior to transmission by thecommunication interface to the server.
 15. The asset tracking device ofclaim 12, further comprising: a sensor to gather sensor data at theasset tracking device; and a locating device to obtain location data ofthe asset tracking device; wherein the data source comprises the sensor,the locating device, or an onboard diagnostic port of the asset, andwherein the interface layer comprises a first interface to obtain thesensor data from the sensor, a second interface to obtain the locationdata from the locating device, and a third interface to obtain assetdata from the onboard diagnostic port.
 16. A non-transitorymachine-readable storage medium comprising instructions that whenexecuted cause a controller of an asset tracking device to: obtain rawdata from a data source onboard an asset; monitor the raw data forsatisfaction of a simplified data capture trigger; when the simplifieddata capture trigger is satisfied, perform a dataset simplificationalgorithm on the raw data to generate a simplified set of raw data, andlog the simplified set of raw data; monitor the raw data forsatisfaction of a rich data capture trigger; when the rich data capturetrigger is satisfied, identify and log an unsimplified block of raw datafor rich data analysis, the unsimplified block of raw data spanning adata window that covers a time at which the rich data capture triggerwas satisfied, the unsimplified block of raw data containing raw datathat is additional to the raw data contained in the simplified set ofraw data; and transmit the simplified set of raw data and theunsimplified block of raw data to a server.
 17. The non-transitorymachine-readable storage medium of claim 16, wherein the instructionsfurther cause the controller to: monitor the raw data for satisfactionof the rich data capture trigger by evaluating the rich data capturetrigger for a first data type; wherein the unsimplified block of rawdata comprises raw data of the first data type.
 18. The non-transitorymachine-readable storage medium of claim 17, wherein evaluation of therich data capture trigger comprises one or more of: determining whethera value of a data point in the raw data of the first data type surpassesa first threshold value; and determining whether a composite value of agroup of data points in the raw data of the first data type that spansan evaluation window surpasses a second threshold value.
 19. Thenon-transitory machine-readable storage medium of claim 17, wherein theunsimplified block of raw data further comprises raw data of a seconddata type different from the first data type.
 20. The non-transitorymachine-readable storage medium of claim 16, wherein the simplified setof raw data is to be processed for telematics services, and wherein theinstructions are further to cause the controller to flag theunsimplified block of raw data for rich data analysis separate fromprocessing of the simplified set of raw data for the telematicsservices.